Five Ways to “Best Test” Recommendation Technology

Product or content recommendation technology enables companies to more easily and more efficiently meet consumer desires and expectations. The result is often a win-win: an uptick in sales as well as in customer satisfaction. That’s because product recommendation software is a solution that helps refine, understand and sometimes even anticipate a shopper’s needs; it’s a filtering process, if you will.

But if you’re a business, how do you filter through the many companies offering these solutions and pick the one that best fits your needs? To help guide you in your decision-making, here are five areas to consider:

Integration - Make sure the solution you’re considering can run on your ecommerce platform. Or if the technology can’t run on your current platform, it must be a solution that can be cost-effectively integrated to do so. Integration should be easy and fast and, if needed, immediate. Look for a solution that requires minimal start-up time. And if possible, avoid products that might require a lengthy burn-in period. In sales, time is critical and once you decide to automate you’ll want the solution to begin making recommendations to your customers as soon as possible.

Personalization – “One-to-One” marketing is a concept popularized by Don Peppers and Martha Rogers in their 1996 groundbreaking book on the topic. But it hasn’t been truly practical for retailers until the arrival of product recommendation technology. And from what we know, consumers appreciate it. Forrester Research reports that 52% of those who have experienced personalization, such as when a store remembers their name, like it. Although all recommendation technology providers will claim to support some level of personalization, make sure it’s a true one-to-one personalization solution—a unique, relevant and dynamic recommendation for every customer—and not just a segmentation solution same lines, look for a solution that can deliver effective recommendations, even that pushes a broad mix of “similar” products at a customer without factoring in what a customer is really looking to buy. Along these when based on limited customer or sales history.

Customization – Recommendation tools typically use proprietary algorithms in combination with several data inputs, such as individual shopping history and product category. The best solutions, however, are customizable; they are flexible enough to work with your current pre-defined business rules. For example, you could add a rule that drives the customer deeper into your product catalog. The option to fine-tune an out-of-the-box recommendation tool can make a huge difference when trying to match the right product with the right customer at the right time.

Operation - It’s indispensable to be able to see exactly what your website visitors will see. Many vendors offer a dashboard that enables previewing of how their product and content recommendation solution is working in a live environment. Don’t overlook this quality assurance capability. You get a chance to make sure the system is functioning as desired. And if it is not operating as planned, it should be easy for you to recommend changes, as well as ensure those changes are implemented in a timely fashion.

Distribution - Ask if the automated recommendations the software generates will be limited to your website. Serious shoppers don’t always begin or end with a company’s website and your product recommendations shouldn’t, either. Ideally, you should be able to distribute these automated recommendations wherever you are engaging customers: website, emails, mobile phones and tablets, social media sites, call centers, and in-store kiosks.

Thinking of automating your product recommendation process? Most likely, you won’t have time to stress test the many solutions offered by vendors. But by incorporating the above five considerations into your evaluation, you will go a long way toward ensuring you’ve picked the right vendor for your needs. And with so many choices out there, you’ll want to make sure you’ve implemented the best one.

Ken Levy, PhD, is CEO and co-founder of 4-Tell, a technology company that increases conversion, sales and revenue for online retailers with personalized product recommendations. An acknowledged thought leader in the rapidly evolving space of cross-channel personalization, Ken is passionate about helping merchants provide online shoppers the best experience possible. 4-Tell has partnered with 3dcart so plugging in Boost® Recommendations for Web is free. Pricing is based on usage, starting at just $49/mo. You can reach him at Ken@4-Tell.com.